Summary

Robocop is a static code analysis and formatting tool specifically designed for the Robot Framework language. It aims to help developers and testers improve code quality, identify potential errors, and enforce consistent coding standards, ultimately leading to more maintainable and trustworthy Robot Framework projects.

How It Works

Robocop leverages the official Robot Framework parsing API to accurately parse Robot Framework code files. It then applies a suite of checks to identify linting issues, potential errors, and violations of established code quality standards. Beyond analysis, it also offers code formatting capabilities to ensure consistency.

Quick Start & Requirements

• Installation: pip install -U robotframework-robocop
• Prerequisites: Python 3.9+ and Robot Framework 4.0+.
• MCP Server: Install with pip install robotframework-robocop[mcp] and run via robocop-mcp.
• Documentation: Full documentation is available at https://robocop.dev.
• IDE Integration: Integrates with PyCharm and VSCode via the RobotCode plugin (https://robotcode.io/).

Highlighted Details

• Features an MCP (Model Context Protocol) server for direct integration with AI assistants like Claude and GitHub Copilot for linting and formatting.
• Supports flexible configuration via TOML files (pyproject.toml, robocop.toml, robot.toml), allowing customization of rules, severity, and formatting options.
• Enables defining custom rules in Python files and supports inline rule suppression (# robocop: off).
• Designed for CI/CD integration, capable of generating reports compatible with platforms such as GitHub, GitLab, and SonarQube.

Maintenance & Community

The provided README does not contain specific details regarding notable contributors, sponsorships, community channels (e.g., Discord, Slack), or a public roadmap.

Licensing & Compatibility

The README does not explicitly state the project's license. This omission requires further investigation before commercial use or integration into closed-source projects.

Limitations & Caveats

No explicit limitations or known issues are detailed in the provided README. The absence of a clearly stated license is a significant caveat for adoption.